Hanwoo Korean Cattle Research Articles

PSVII-9 Improvement of feed efficiency in Korean Hanwoo cattle: investigation of feed intake and analysis of residual feed intake (RFI)

Abstract Feed efficiency is an important economic trait in beef cattle production, and improving feed efficiency can reduce production costs and environmental impact. Residual feed intake (RFI) is a useful measure of individual feed efficiency, representing the difference between the actual feed intake of an animal and its predicted feed intake based on its body weight (BW) and growth. This study aimed to investigate feed intake and analyze RFI in Hanwoo cattle to improve feed efficiency. Data were collected from 120 Hanwoo steers (9 to 11 mo old) from six different test stations across the country. Individual daily feed intake of concentrates and forage was recorded over 70 d, and BW was measured at the beginning and end of the feeding trial. Daily feed intake was calculated using the TDN values of the concentrates and forage. Expected feed intake was estimated using a linear regression model based on metabolic BW and daily gain. RFI was calculated as the difference between expected and actual feed intake. Average daily gain ranged from 1.05 to 1.71 kg/d, and average daily feed intake ranged from 5.10 to 7.72 kg/d across the test stations. RFI values ranged from -0.84 to 0.95 kg/d, indicating significant variation in feed efficiency among the animals. This study provides valuable information on feed intake and RFI in Hanwoo cattle. Further research with a larger dataset is needed to develop a genetic evaluation model for RFI and to select animals with superior feed efficiency for improving Hanwoo cattle production.

Evaluation of non-additive genetic effects on carcass and meat quality traits in Korean Hanwoo cattle using genomic models

The traditional genetic evaluation methods generally consider additive genetic effects only and often ignore non-additive (dominance and epistasis) effects that may have contributed to genetic variation of complex traits of livestock species. The available dense single nucleotide polymorphisms (SNPs) panels offer to investigate the potential benefits of including non-additive genetic effects in the genomic evaluation models. Data from 16 971 genotyped (Illumina Bovine 50 K SNP chip) Korean Hanwoo cattle were used to estimate genetic variance components and prediction accuracy of genomic breeding values (GEBVs) for four carcass and meat quality traits: carcass weight (CWT), eye muscle area (EMA), back fat thickness (BFT) and marbling score (MS). Five different genetic models were evaluated through including additive, dominance and epistatic interactions (additive by additive, A × A; additive by dominance, A × D and dominance by dominance, D × D) successively in the models. The estimates of additive genetic variances and narrow sense heritabilities (ha2) were found similar across the evaluated models and traits except when additive interaction (A × A) was included. The dominance variance estimates relative to phenotypic variance ranged from 1.7–3.4% for CWT and MS traits, whereas, they were close to zero for EMA and BFT traits. The magnitude of A × A epistatic heritability (haa2) ranged between 14.8 and 27.7% in all traits. However, heritability estimates for A × D and D × D epistatic interactions (had2 and hdd2) were quite low compared to haa2 and were contributed only 0.0–9.7% of the total phenotypic variation. In general, broad sense heritability (hG2) estimates were almost twice (ranging between 0.54 and 0.68) the ha2 for all of the investigated traits. The inclusion of dominance effects did not improve the prediction accuracy of GEBV but improved 2.0–3.0% when epistatic effects were included in the model. More importantly, rank correlation revealed that partitioning of variance components considering dominance and epistatic effects in the model would enable to re-rank of top animals with better prediction of GEBV. The present result suggests that dominance and epistatic effects could be included in the genomic evaluation model for better estimates of variance components and more accurate prediction of GEBV for carcass and meat quality traits in Korean Hanwoo cattle.

Comparative Pharmacokinetics and Bioequivalence of Pour-On Ivermectin Formulations in Korean Hanwoo Cattle.

This study aimed to conduct a bioequivalence study of applying three pour-on ivermectin formulations at a dose of 1 mg/kg on the back of Korean native beef cattle (Hanwoo). To conduct bioequivalence testing, the pharmacokinetics of three groups (control Innovator, test Generic A, and test Generic B) of five clinically healthy Korean Hanwoo cattle (average weight 500 kg) were studied. After topical application to the skin, blood samples were drawn at the indicated times. These blood samples were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The time required to reach the maximum concentration (Tmax), the maximum concentration (Cmax), and the area under the curve (AUClast) of each pharmacokinetic parameter were compared for bioequivalence. The results showed that the control had a Tmax of 41 ± 1.24 h, a Cmax of 0.11 ± 0.01 μg/mL, and an AUClast of 9.33 ± 0 h*μg/mL). The comparator Generic A had a Tmax of 40 ± 1.14 h, a Cmax of 0.10 ± 0.01 (μg/mL, and an AUClast of 9.41 ± 0.57 h*μg/mL, while Generic B had a Tmax of 40 ± 2.21 h, a Cmax of 0.10 ± 0.01 μg/mL, and an AUClast of 9 h*μg/mL. The values of the bioequivalence indicators Cmax, Tmax, and AUC were all within the range of 80% to 120%, confirming that all three tested formulations were bioequivalent. In conclusion, the study showed that the two generic products were bioequivalent to the original product in Hanwoo cattle.

Parameter estimation and assessment of bias in genetic evaluation of carcass traits in Hanwoo cattle using real and simulated data.

Most carcass and meat quality traits are moderate to highly heritable, indicating that they can be improved through selection. Genetic evaluation for these types of traits is performed using performance data obtained from commercial and progeny testing evaluation. The performance data from commercial farms are available in large volume, however, some drawbacks have been observed. The drawback of the commercial data is mainly due to sorting of animals based on live weight prior to slaughter, and this could lead to bias in the genetic evaluation of later measured traits such as carcass traits. The current study has two components to address the drawback of the commercial data. The first component of the study aimed to estimate genetic parameters for carcass and meat quality traits in Korean Hanwoo cattle using a large sample size of industry-based carcass performance records (n = 469,002). The second component of the study aimed to describe the impact of sorting animals into different contemporary groups based on an early measured trait and then examine the effect on the genetic evaluation of subsequently measured traits. To demonstrate our objectives, we used real performance data to estimate genetic parameters and simulated data was used to assess the bias in genetic evaluation. The results of our first study showed that commercial data obtained from slaughterhouses is a potential source of carcass performance data and useful for genetic evaluation of carcass traits to improve beef cattle performance. However, we observed some harvesting effect which leads to bias in genetic evaluation of carcass traits. This is mainly due to the selection of animal based on their body weight before arrival to slaughterhouse. Overall, the non-random allocation of animals into a contemporary group leads to a biased estimated breeding value in genetic evaluation, the severity of which increases when the evaluation traits are highly correlated.

Evaluation of Whole-Genome Sequence Imputation Strategies in Korean Hanwoo Cattle.

Simple SummaryIn this study, we evaluated various imputation strategies for the Korean Hanwoo cattle. We observed that a large reference panel consisting of many cattle breeds did not improve the imputation accuracy when compared to a proportionally small purebred Hanwoo reference. This was because the multi-breed reference did not contain animals sufficiently related to the Hanwoo to improve the accuracies and, although not detrimental, in effect, only added to the computational burden of the imputation. Despite the large multi-breed reference, when the Hanwoo were removed from the reference, the imputation accuracies were low. These results suggest additional sequencing efforts are needed for underrepresented breeds, particularly those less genetically related to the main European breeds.This study evaluated the accuracy of sequence imputation in Hanwoo beef cattle using different reference panels: a large multi-breed reference with no Hanwoo (n = 6269), a much smaller Hanwoo purebred reference (n = 88), and both datasets combined (n = 6357). The target animals were 136 cattle both sequenced and genotyped with the Illumina BovineSNP50 v2 (50K). The average imputation accuracy measured by the Pearson correlation (R) was 0.695 with the multi-breed reference, 0.876 with the purebred Hanwoo, and 0.887 with the combined data; the average concordance rates (CR) were 88.16%, 94.49%, and 94.84%, respectively. The accuracy gains from adding a large multi-breed reference of 6269 samples to only 88 Hanwoo was marginal; however, the concordance rate for the heterozygotes decreased from 85% to 82%, and the concordance rate for fixed SNPs in Hanwoo also decreased from 99.98% to 98.73%. Although the multi-breed panel was large, it was not sufficiently representative of the breed for accurate imputation without the Hanwoo animals. Additionally, we evaluated the value of high-density 700K genotypes (n = 991) as an intermediary step in the imputation process. The imputation accuracy differences were negligible between a single-step imputation strategy from 50K directly to sequence and a two-step imputation approach (50K-700K-sequence). We also observed that imputed sequence data can be used as a reference panel for imputation (mean R = 0.9650, mean CR = 98.35%). Finally, we identified 31 poorly imputed genomic regions in the Hanwoo genome and demonstrated that imputation accuracies were particularly lower at the chromosomal ends.

Genomic Prediction Based on SNP Functional Annotation Using Imputed Whole-Genome Sequence Data in Korean Hanwoo Cattle.

Whole-genome sequence (WGS) data are increasingly being applied into genomic predictions, offering a higher predictive ability by including causal mutations or single-nucleotide polymorphisms (SNPs) putatively in strong linkage disequilibrium with causal mutations affecting the trait. This study aimed to improve the predictive performance of the customized Hanwoo 50 k SNP panel for four carcass traits in commercial Hanwoo population by adding highly predictive variants from sequence data. A total of 16,892 Hanwoo cattle with phenotypes (i.e., backfat thickness, carcass weight, longissimus muscle area, and marbling score), 50 k genotypes, and WGS imputed genotypes were used. We partitioned imputed WGS data according to functional annotation [intergenic (IGR), intron (ITR), regulatory (REG), synonymous (SYN), and non-synonymous (NSY)] to characterize the genomic regions that will deliver higher predictive power for the traits investigated. Animals were assigned into two groups, the discovery set (7324 animals) used for predictive variant detection and the cross-validation set for genomic prediction. Genome-wide association studies were performed by trait to every genomic region and entire WGS data for the pre-selection of variants. Each set of pre-selected SNPs with different density (1000, 3000, 5000, or 10,000) were added to the 50 k genotypes separately and the predictive performance of each set of genotypes was assessed using the genomic best linear unbiased prediction (GBLUP). Results showed that the predictive performance of the customized Hanwoo 50 k SNP panel can be improved by the addition of pre-selected variants from the WGS data, particularly 3000 variants from each trait, which is then sufficient to improve the prediction accuracy for all traits. When 12,000 pre-selected variants (3000 variants from each trait) were added to the 50 k genotypes, the prediction accuracies increased by 9.9, 9.2, 6.4, and 4.7% for backfat thickness, carcass weight, longissimus muscle area, and marbling score compared to the regular 50 k SNP panel, respectively. In terms of prediction bias, regression coefficients for all sets of genotypes in all traits were close to 1, indicating an unbiased prediction. The strategy used to select variants based on functional annotation did not show a clear advantage compared to using whole-genome. Nonetheless, such pre-selected SNPs from the IGR region gave the highest improvement in prediction accuracy among genomic regions and the values were close to those obtained using the WGS data for all traits. We concluded that additional gain in prediction accuracy when using pre-selected variants appears to be trait-dependent, and using WGS data remained more accurate compared to using a specific genomic region.

Genetic diversity and differentiation among Korean-Holstein, Hanwoo, and Uganda-Holstein breeds

The aim of this research was to assess genetic diversity of Korean-Holstein, Korean Hanwoo, and Ugandan-Holstein dairy cattle. DNA was extracted from either blood or hair of Korean-Holstein (n=74), Korean-Hanwoo (n=75) and Ugandan-Holstein (N=77) using AccuPrep® PCR purification kit. The DNA samples were amplified by multiplex polymerase chain reaction, using GeneTrackTM Hanwoo genotyping kit and assayed using ABI genetic analyser 3130XL. Number of alleles, expected heterozygosity (He), observed heterozygosity (Ho), and the polymorphism information content (PIC) were estimated from 10 microsatellite loci in the three breeds. In addition, F-statistics for each of the 10 microsatellites in the three cattle breeds were estimated using fstat version 2.9.3.2 computer program. GENETIX (v.4.02) was used to perform factorial correspondence analysis (FCA) from the allele frequencies and multi-locus clustering was done using STRUCTURE analyses. A total of 124 alleles were detected. The number of alleles per locus varied from eight (TGLA126) to 22 (TGLA122), with an overall mean of 12.2. Expected heterozygosity ranged from 0.617 (SPS115) to 0.854 (TGLA53) and averaged 0.761. Observed heterozygosity ranged from 0.6 (SPS115) to 0.859 (TGLA53); and averaged 0.761. The mean PIC was 0.723; and means of the F-statistics FIT, FST and FIS were 0.077, 0.076 and 0.001 respectively. Although FCA revealed clear differentiation of Uganda-Holstein, Korean-Holstein, and Hanwoo, clustering assignments showed genetic admixture between Ugandan dairy cattle (Uganda-Holstein) and Hanwoo. In conclusion, the allelic variation present at the 10 loci was sufficient to categorize these cattle into distinct breed groups.
 Keywords: dairy cattle, genetic differentiation, F-statistics, heterozygosity, microsatellite

Prediction of marbling score and carcass traits in Korean Hanwoo beef cattle using machine learning methods and synthetic minority oversampling technique

Pricing of Hanwoo beef in the Korean market is primarily based on meat quality, and particularly on marbling score. The ability to accurately predict marbling score early in the life of an animal is extremely valuable for producers to meet the requirements of their target market, and for genetic selection. A total of 3989 Korean Hanwoo cattle (2108 with 50 k SNP genotypes) and 45 phenotypic features were available for this study. Four machine learning (ML) algorithms were applied to predict six carcass traits and compared against linear regression prediction models. In most scenarios, SMO was the best performing algorithm. The most and least accurately predicted traits were carcass weight and marbling score with correlation of 0.95 and 0.64 respectively. Additionally, the value of using a synthetic minority over-sampling technique (SMOTE) was evaluated and results showed a slight improvement in the prediction error of marbling score. Machine Learning approaches can be useful tools to predict important carcass traits in beef cattle.

Effect of errors in pedigree on the accuracy of estimated breeding value for carcass traits in Korean Hanwoo cattle.

ObjectiveThis study evaluated the effect of pedigree errors (PEs) on the accuracy of estimated breeding value (EBV) and genetic gain for carcass traits in Korean Hanwoo cattle.MethodsThe raw data set was based on the pedigree records of Korean Hanwoo cattle. The animals’ information was obtained using Hanwoo registration records from Korean animal improvement association database. The record comprised of 46,704 animals, where the number of the sires used was 1,298 and the dams were 38,366 animals. The traits considered were carcass weight (CWT), eye muscle area (EMA), back fat thickness (BFT), and marbling score (MS). Errors were introduced in the pedigree dataset through randomly assigning sires to all progenies. The error rates substituted were 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, and 80%, respectively. A simulation was performed to produce a population of 1,650 animals from the pedigree data. A restricted maximum likelihood based animal model was applied to estimate the EBV, accuracy of the EBV, expected genetic gain, variance components, and heritability (h2) estimates for carcass traits. Correlation of the simulated data under PEs was also estimated using Pearson’s method.ResultsThe results showed that the carcass traits per slaughter year were not consistent. The average CWT, EMA, BFT, and MS were 342.60 kg, 78.76 cm2, 8.63 mm, and 3.31, respectively. When errors were introduced in the pedigree, the accuracy of EBV, genetic gain and h2 of carcass traits was reduced in this study. In addition, the correlation of the simulation was slightly affected under PEs.ConclusionThis study reveals the effect of PEs on the accuracy of EBV and genetic parameters for carcass traits, which provides valuable information for further study in Korean Hanwoo cattle.

PSIV-15 Interaction between E+ and Abr loci is associated with brindle coat color in Korean Hanwoo cattle.

PSIV-15 Interaction between E+ and Abr loci is associated with brindle coat color in Korean Hanwoo cattle.

Genome-wide association study and prediction of genomic breeding values for fatty-acid composition in Korean Hanwoo cattle using a high-density single-nucleotide polymorphism array.

Genomic selection using high-density single-nucleotide polymorphism (SNP) markers is used in dairy and beef cattle breeds to accurately estimate genomic breeding values and accelerate genetic improvement by enabling selection of animals with high genetic merit. This genome-wide association study (GWAS) aimed to identify genetic variants associated with beef fatty-acid composition (FAC) traits and to evaluate the accuracy of genomic predictions (GPs) for those traits using genomic best linear unbiased prediction (GBLUP), pedigree BLUP (PBLUP), and BayesR models. Samples of the longissimus dorsi muscle of 965 thirty-month-old Hanwoo steers (progeny of 73 proven bulls) were used to investigate 14 FAC traits. Animals were genotyped or imputed using two bovine SNP platforms (50K and 777K), and after quality control, 38,715 (50K) and 633,448 (777K) SNPs were subjected to GWAS and GP study using a cross-validation scheme. SNP-based heritability estimates were moderate to high (0.25 to 0.47) for all studied traits, with some exceptions for polyunsaturated fatty acids. Association analysis revealed that 19 SNPs in BTA19 (98.7 kb) were significantly associated (P < 7.89 × 10-8) with C14:0 and C18:1n-9; these SNPs were in the fatty-acid synthase (FASN) and coiled-coil domain-containing 57 (CCDC57) genes. BayesR analysis revealed that 0.41 to 0.78% of the total SNPs (n = 2,571 to 4,904) explained almost all of the genetic variance; the majority of the SNPs (>99%) had negligible effects, suggesting that the FAC traits were polygenic. Genome partitioning analysis indicated mostly nonlinear and weak correlations between the variance explained by each chromosome and its length, which also reflected the considerable contributions of relatively few genes. The prediction accuracy of breeding values for FAC traits varied from low to high (0.25 to 0.57); the estimates using the GBLUP and BayesR methods were superior to those obtained by the PBLUP method. The BayesR method performed similarly to GBLUP for most of the studied traits but substantially better for those traits that were controlled by SNPs with large effects; this was supported by the GWAS results. In addition, the predictive abilities of the 50K and 777K SNP arrays were almost similar; thus, both are suitable for GP in Hanwoo cattle. In conclusion, this study provides important insight into the genetic architecture and predictive ability of FAC traits in Hanwoo cattle. Our findings could be used in selection and breeding programs to promote production of meat with enhanced nutritional value.

Loin eye muscle physico-chemical attributes, sensory evaluation and proximate composition in Korean Hanwoo cattle subjected to slaughtering along with stunning with or without pithing

Korean Hanwoo Cattle (KHC) were utilized to compare existing and modified methods of slaughtering. Carcass traits, loin eye muscle color coordination, physico-chemical attributes, sensory evaluation and proximate composition were assessed. Twelve KHC were slaughtered following 1) CSNHS: non-halal way neck cutting as following captive bolt stunning with pithing and 2) CSHS: halal way neck cutting as following captive bolt stunning without pithing. Loin eye muscle color coordination, physico-chemical attributes and sensory evaluation did not differ significantly subjected to slaughter types (P > 0.05). However, loin eye muscle crude ash content was higher in CSHS group relative to CSNHS (P < 0.05). Pearson’s correlation analysis indicated that several traits were affected by slaughter types. Overall, CSHS ensures no negative impact on meat yield and qualitative traits rather led a higher loin eye muscle crude ash content. Therefore, CSHS could be adopted in Korean slaughterhouses with modification of existing practice.

Functional Partitioning of Genomic Variance and Genome-Wide Association Study for Carcass Traits in Korean Hanwoo Cattle Using Imputed Sequence Level SNP Data

Quantitative traits are usually controlled by numerous genomic variants with small individual effects, and variances associated with those traits are explained in a continuous manner. However, the relative contributions of genomic regions to observed genetic variations have not been well explored using sequence level single nucleotide polymorphism (SNP) information. Here, imputed sequence level SNP data (11,278,153 SNPs) of 2109 Hanwoo steers (Korean native cattle) were partitioned according to functional annotation, chromosome, and minor allele frequency (MAF). Genomic relationship matrices (GRMs) were constructed for each classified region and fitted in the model both separately and together for carcass weight (CWT), eye muscle area (EMA), backfat thickness (BFT), and marbling score (MS) traits. A genome-wide association study (GWAS) was performed to identify significantly associated variants in genic and exon regions using a linear mixed model, and the genetic contribution of each exonic SNP was determined using a Bayesian mixture model. Considering all SNPs together, the heritability estimates for CWT, EMA, BFT, and MS were 0.57 ± 0.05, 0.46 ± 0.05, 0.45 ± 0.05, and 0.49 ± 0.05, respectively, which reflected substantial genomic contributions. Joint analysis revealed that the variance explained by each chromosome was proportional to its physical length with weak linear relationships for all traits. Moreover, genomic variances explained by functional category and MAF class differed greatly among the traits studied in joint analysis. For example, exon regions had larger contributions for BFT (0.13 ± 0.08) and MS (0.22 ± 0.08), whereas intron and intergenic regions explained most of the total genomic variances for CWT and EMA (0.22 ± 0.09–0.32 ± 0.11). Considering different functional classes of exon regions and the per SNP contribution revealed the largest proportion of genetic variance was attributable to synonymous variants. GWAS detected 206 and 27 SNPs in genic and exon regions, respectively, on BTA4, BTA6, and BTA14 that were significantly associated with CWT and EMA. These SNPs were harbored by 31 candidate genes, among which TOX, FAM184B, PPARGC1A, PRKDC, LCORL, and COL1A2 were noteworthy. BayesR analysis found that most SNPs (>93%) had very small effects and the 4.02–6.92% that had larger effects (10-4 × , 10-3 × , and 10-2 × ) explained most of the total genetic variance, confirming polygenic components of the traits studied.

Genome sequencing and protein domain annotations of Korean Hanwoo cattle identify Hanwoo-specific immunity-related and other novel genes

BackgroundIdentification of genetic mechanisms and idiosyncrasies at the breed-level can provide valuable information for potential use in evolutionary studies, medical applications, and breeding of selective traits. Here, we analyzed genomic data collected from 136 Korean Native cattle, known as Hanwoo, using advanced statistical methods.ResultsResults revealed Hanwoo-specific protein domains which were largely characterized by immunoglobulin function. Furthermore, domain interactions of novel Hanwoo-specific genes reveal additional links to immunity. Novel Hanwoo-specific genes linked to muscle and other functions were identified, including protein domains with functions related to energy, fat storage, and muscle function that may provide insight into the mechanisms behind Hanwoo cattle’s uniquely high percentage of intramuscular fat and fat marbling.ConclusionThe identification of Hanwoo-specific genes linked to immunity are potentially useful for future medical research and selective breeding. The significant genomic variations identified here can crucially identify genetic novelties that are arising from useful adaptations. These results will allow future researchers to compare and classify breeds, identify important genetic markers, and develop breeding strategies to further improve significant traits.

Estimates of genetic parameters for fatty acid compositions in the longissimus dorsi muscle of Hanwoo cattle

We estimated the heritabilities (h2) and genetic and phenotypic correlations among individual and groups of fatty acids, as well as their correlations with six important carcass and meat-quality traits in Korean Hanwoo cattle. Meat samples were collected from the longissimus dorsi muscles of 1000 Hanwoo steers that were 30-month-old (progeny of 85 proven Hanwoo bulls) to determine intramuscular fatty acid profiles. Phenotypic data on carcass weight (CWT), eye muscle area (EMA), back fat thickness (BFT), marbling score (MS), Warner–Bratzler shear force (WBSF) and intramuscular fat content (IMF) were also investigated using this half-sib population. Variance and covari.ance components were estimated using restricted maximum likelihood procedures under univariate and pairwise bivariate animal models. Oleic acid (C18:1n-9) was the most abundant fatty acid, accounting for 50.69% of all investigated fatty acids, followed by palmitic (C16:0; 27.33%) and stearic acid (C18:0; 10.96%). The contents of saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs) and polyunsaturated fatty acids (PUFAs) were 41.64%, 56.24% and 2.10%, respectively, and the MUFA/SFA ratio, PUFA/SFA ratio, desaturation index (DI) and elongation index (EI) were 1.36, 0.05, 0.59 and 0.66, respectively. The h2 estimates for individual fatty acids ranged from very low to high (0.03±0.14 to 0.63±0.14). The h2 estimates for SFAs, MUFAs, PUFAs, DI and EI were 0.53±0.14, 0.49±0.14, 0.23±0.10, 0.51±0.13 and 0.53±0.13, respectively. The genetic and phenotypic correlations among individual fatty acids and fatty acid classes varied widely (−0.99 to 0.99). Notably, C18:1n-9 had favourable (negative) genetic correlations with two detrimental fatty acids, C14:0 (−0.76) and C16:0 (−0.92). Genetic correlations of individual and group fatty acids with CWT, EMA, BFT, MS, WBSF and IMF ranged from low to moderate (both positive and negative) with the exception of low-concentration PUFAs. Low or near-zero phenotypic correlations reflected potential non-genetic contributions. This study provides insights on genetic variability and correlations among intramuscular fatty acids as well as correlations between fatty acids and carcass and meat-quality traits, which could be used in Hanwoo breeding programmes to improve fatty acid compositions in meat.

Genetic parameters of carcass and meat quality traits in different muscles (longissimus dorsi and semimembranosus) of Hanwoo (Korean cattle).

We estimated heritability () and genetic and phenotypic correlations for carcass and meat quality traits of longissimus dorsi (LD) and semimembranosus (SM) muscles in 30-mo-old Hanwoo steers. Variance and covariance components were estimated using REML procedures under univariate and bivariate models. The mean carcass weight (CWT), eye muscle area (EMA), back fat thickness (BFT), and marbling score (MS) were 428.20 ± 46.30 kg, 87.38 ± 8.54 cm2, 13.00 ± 5.14 mm, and 5.21 ± 1.56, respectively. The mean CIE reflectance of meat lightness (L*), redness (a*), and yellowness (b*) were 40.01 ± 2.73, 22.37 ± 2.18, and 10.35 ± 1.46, respectively, in LD muscles and 36.33 ± 2.44, 22.91 ± 2.43, and 10.25 ± 1.65, respectively, in SM muscles. The mean Warner-Bratzler shear force (WBSF), intramuscular fat content (IMF), water-holding capacity (WHC), and protein and ash content in LD and SM muscles were 3.84 ± 0.96 and 6.52 ± 1.21 kg, 15.91 ± 4.39 and 5.10 ± 1.94%, 62.07 ± 3.38 and 71.61 ± 2.06%, 20.01 ± 1.39 and 21.34 ± 0.89%, and 0.80 ± 0.10 and 0.93 ± 0.07, respectively. The estimates of CWT, EMA, BFT, and MS were 0.51 ± 0.13, 0.45 ± 0.13, 0.29 ± 0.09, and 0.22 ± 0.08, respectively. The estimates were moderate for meat quality traits and were 0.37 ± 0.12, 0.40 ± 0.12, 0.33 ± 0.10, 0.33 ± 0.10, 0.30 ± 0.11, and 0.24 ± 0.09 for L*, WBSF, IMF, WHC, and protein and ash content, respectively, in LD muscle; estimates from SM muscle were comparatively low (0.08 ± 0.06 to 0.25 ± 0.09). Estimates of for a* and b* were also low (0.08 ± 0.06 to 0.13 ± 0.07). Carcass weight had a moderate, positive genetic correlation with EMA (0.60 ± 0.13) and a weak correlation with MS and BFT. The genetic correlations among the 3 colorimeter variants were strong and positive within and between muscles. Intramuscular fat content had moderate to strong and negative genetic correlations with WBSF (-0.49 ± 0.18), WHC (-0.99 ± 0.01), and protein (-0.93 ± 0.04) and ash content (-0.98 ± 0.06) in LD muscle, whereas the associations were less pronounced in SM muscle. In general, CWT and EMA had low genetic and phenotypic correlations with meat quality traits, which suggests that the traits are independent and have distinct genetic contributions in each muscle. Conversely, with few exceptions, meat quality traits had genetic and phenotypic correlations with MS and BFT. In conclusion, the estimated genetic parameters for carcass and meat quality traits could be used for genetic evaluation and breeding programs in Korean Hanwoo cattle populations.

Marbling and Its Nutritional Impact on Risk Factors for Cardiovascular Disease.

This review addresses the role of fat in beef palatability and healthfulness. Particular emphasis is placed on the content of oleic acid in beef, and how this increases with time when cattle are fed a grain-based diet. Oleic acid decreases the melting point of lipids from beef, increasing the perception of juiciness and improving beef flavor. Clinical trials have demonstrated that ground beef containing elevated oleic acid increases, or at the least has no negative effects on the concentration of HDL cholesterol. The amount of fat in published ground beef intervention trials greatly exceeds the amount of fat in equivalent portions of beef from U.S. domestic or Korean Hanwoo cattle. Thus, we conclude 1) Beef cattle should be raised under production conditions that increase the concentration of oleic acid in their edible tissues (i.e., by grain feeding over extended periods of time); and 2) The amount of fat consumed in a typical portion of beef will not increase risk factors for cardiovascular disease.

Genomic Footprints in Selected and Unselected Beef Cattle Breeds in Korea.

Korean Hanwoo cattle have been subjected to intensive artificial selection over the past four decades to improve meat production traits. Another three cattle varieties very closely related to Hanwoo reside in Korea (Jeju Black and Brindle) and in China (Yanbian). These breeds have not been part of a breeding scheme to improve production traits. Here, we compare the selected Hanwoo against these similar but presumed to be unselected populations to identify genomic regions that have been under recent selection pressure due to the breeding program. Rsb statistics were used to contrast the genomes of Hanwoo versus a pooled sample of the three unselected population (UN). We identified 37 significant SNPs (FDR corrected) in the HW/UN comparison and 21 known protein coding genes were within 1 MB to the identified SNPs. These genes were previously reported to affect traits important for meat production (14 genes), reproduction including mammary gland development (3 genes), coat color (2 genes), and genes affecting behavioral traits in a broader sense (2 genes). We subsequently sequenced (Illumina HiSeq 2000 platform) 10 individuals of the brown Hanwoo and the Chinese Yanbian to identify SNPs within the candidate genomic regions. Based on allele frequency differences, haplotype structures, and literature research, we singled out one non-synonymous SNP in the APP gene (APP: c.569C>T, Ala199Val) and predicted the mutational effect on the protein structure. We found that protein-protein interactions might be impaired due to increased exposed hydrophobic surfaces of the mutated protein. The APP gene has also been reported to affect meat tenderness in pigs and obesity in humans. Meat tenderness has been linked to intramuscular fat content, which is one of the main breeding goals for brown Hanwoo, potentially supporting a causal influence of the herein described nsSNP in the APP gene.

Methanogenic archaea diversity in Hanwoo (Bos taurus coreanae) rumen fluid, rectal dung, and barn floor manure using a culture-independent method based on mcrA gene sequences

The diversity of methanogenic archaea associated with Korean Hanwoo cattle was analyzed using mcrA gene sequences from samples of rumen fluid (RF), rectal dung (RD), and barn floor manure (BFM). The predominant species were Methanobrevibacter ruminantium in RF and BFM(63.6% and 62.4%, respectively) and Methanocorpusculum labreanum in RD (53.2%).

Genome‐wide detection of signatures of selection in Korean Hanwoo cattle

The Korean Hanwoo cattle have been intensively selected for production traits, especially high intramuscular fat content. It is believed that ancient crossings between different breeds contributed to forming the Hanwoo, but little is known about the genomic differences and similarities between other cattle breeds and the Hanwoo. In this work, cattle breeds were grouped by origin into four types and used for comparisons: the Europeans (represented by six breeds), zebu (Nelore), African taurine (N'Dama) and Hanwoo. All animals had genotypes for around 680000 SNPs after quality control of genotypes. Average heterozygosity was lower in Nelore and N'Dama (0.22 and 0.21 respectively) than in Europeans (0.26-0.31, with Shorthorn as outlier at 0.24) and Hanwoo (0.29). Pairwise FST analyses demonstrated that Hanwoo are more related to European cattle than to Nelore, with N'Dama in an intermediate position. This finding was corroborated by principal components and unsupervised hierarchical clustering. Using genome-wide smoothed FST , 55 genomic regions potentially under positive selection in Hanwoo were identified. Among these, 29 were regions also detected in previous studies. Twenty-four regions were exclusive to Hanwoo, and a number of other regions were shared with one or two of the other groups. These regions overlap a number of genes that are related to immune, reproduction and fatty acid metabolism pathways. Further analyses are needed to better characterize the ancestry of the Hanwoo cattle and to define the genes responsible to the identified selection peaks.